With the development of data storage technology, significant improvements have been made to the storage capacity of a database system, and thus hundreds of thousands of or even more data entries can be stored in a database. An index is built for the database for improving of the efficiency of data queries in the database, and many approaches for building the index for the database have been proposed so far.
Although the index increases the efficiency of the data queries, additional workloads are required in building the index if data entries are inserted in the database. Further, maintaining the index also costs extra time and computing resources if data entries in the database are modified. Specifically, under some circumstances (for example, if the database is refreshed), all the data entries are deleted and then new data entries are inserted into the database. At this point, the index of the database is deleted together with the data entries in the database during the deleting procedure, and then a new index is built during inserting new data entries into the database. Building a new index is time-consuming and needs extra computing resources.